Overview

Dataset statistics

Number of variables8
Number of observations1414000
Missing cells4831148
Missing cells (%)42.7%
Duplicate rows138
Duplicate rows (%)< 0.1%
Total size in memory86.3 MiB
Average record size in memory64.0 B

Variable types

Numeric8

Alerts

Dataset has 138 (< 0.1%) duplicate rowsDuplicates
altitude is highly overall correlated with timeHigh correlation
latitude is highly overall correlated with velocityHigh correlation
reflectivity is highly overall correlated with total_powerHigh correlation
spectrum_width is highly overall correlated with timeHigh correlation
time is highly overall correlated with altitude and 1 other fieldsHigh correlation
total_power is highly overall correlated with reflectivityHigh correlation
velocity is highly overall correlated with latitudeHigh correlation
reflectivity has 1220984 (86.3%) missing valuesMissing
total_power has 1046362 (74.0%) missing valuesMissing
velocity has 1264638 (89.4%) missing valuesMissing
spectrum_width has 1299164 (91.9%) missing valuesMissing

Reproduction

Analysis started2024-04-22 10:23:27.187092
Analysis finished2024-04-22 10:23:38.215237
Duration11.03 seconds
Software versionydata-profiling vv4.7.0
Download configurationconfig.json

Variables

longitude
Real number (ℝ)

Distinct928070
Distinct (%)65.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.667174
Minimum9.582827
Maximum11.736427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 MiB
2024-04-22T17:23:38.264169image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum9.582827
5-th percentile9.9020188
Q110.395782
median10.663281
Q310.943005
95-th percentile11.425909
Maximum11.736427
Range2.1536
Interquartile range (IQR)0.54722262

Descriptive statistics

Standard deviation0.43556567
Coefficient of variation (CV)0.040832341
Kurtosis-0.27982083
Mean10.667174
Median Absolute Deviation (MAD)0.273649
Skewness-0.015761651
Sum15083383
Variance0.18971745
MonotonicityNot monotonic
2024-04-22T17:23:38.336404image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.65961 2845
 
0.2%
10.659617 74
 
< 0.1%
10.659609 61
 
< 0.1%
10.659618 58
 
< 0.1%
10.659625 45
 
< 0.1%
10.659613 45
 
< 0.1%
10.659626 44
 
< 0.1%
10.659612 40
 
< 0.1%
10.659614 39
 
< 0.1%
10.659611 34
 
< 0.1%
Other values (928060) 1410715
99.8%
ValueCountFrequency (%)
9.582827 1
< 0.1%
9.582888 1
< 0.1%
9.583026 1
< 0.1%
9.583459 1
< 0.1%
9.583496 1
< 0.1%
9.58354 1
< 0.1%
9.583594 1
< 0.1%
9.583719 1
< 0.1%
9.584062 1
< 0.1%
9.584208 1
< 0.1%
ValueCountFrequency (%)
11.736427 1
< 0.1%
11.736286 1
< 0.1%
11.736244 1
< 0.1%
11.735795 1
< 0.1%
11.735745 1
< 0.1%
11.735736 1
< 0.1%
11.73558 1
< 0.1%
11.735578 1
< 0.1%
11.735091 1
< 0.1%
11.735078 1
< 0.1%

latitude
Real number (ℝ)

HIGH CORRELATION 

Distinct263081
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean106.73372
Minimum105.63263
Maximum107.82406
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 MiB
2024-04-22T17:23:38.407377image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum105.63263
5-th percentile105.9504
Q1106.45373
median106.73201
Q3107.01683
95-th percentile107.50838
Maximum107.82406
Range2.19143
Interquartile range (IQR)0.5631

Descriptive statistics

Standard deviation0.44577492
Coefficient of variation (CV)0.0041765143
Kurtosis-0.29988924
Mean106.73372
Median Absolute Deviation (MAD)0.28155
Skewness-0.020378742
Sum1.5092148 × 108
Variance0.19871528
MonotonicityNot monotonic
2024-04-22T17:23:38.485696image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
106.728325 2865
 
0.2%
106.728294 156
 
< 0.1%
106.730515 92
 
< 0.1%
106.72855 92
 
< 0.1%
106.72829 82
 
< 0.1%
106.730446 77
 
< 0.1%
106.7283 75
 
< 0.1%
106.72832 75
 
< 0.1%
106.72828 75
 
< 0.1%
106.728096 75
 
< 0.1%
Other values (263071) 1410336
99.7%
ValueCountFrequency (%)
105.63263 1
< 0.1%
105.63274 1
< 0.1%
105.63286 1
< 0.1%
105.63318 1
< 0.1%
105.63327 1
< 0.1%
105.633385 1
< 0.1%
105.63342 1
< 0.1%
105.633484 1
< 0.1%
105.63381 1
< 0.1%
105.63396 1
< 0.1%
ValueCountFrequency (%)
107.82406 1
< 0.1%
107.82397 1
< 0.1%
107.823814 1
< 0.1%
107.82356 1
< 0.1%
107.82337 1
< 0.1%
107.823265 1
< 0.1%
107.82324 1
< 0.1%
107.82312 1
< 0.1%
107.82285 1
< 0.1%
107.82279 1
< 0.1%

altitude
Real number (ℝ)

HIGH CORRELATION 

Distinct23270
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5616.9502
Minimum10
Maximum25697
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 MiB
2024-04-22T17:23:38.562826image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile242
Q11434
median3774
Q38082
95-th percentile17578
Maximum25697
Range25687
Interquartile range (IQR)6648

Descriptive statistics

Standard deviation5472.9762
Coefficient of variation (CV)0.97436794
Kurtosis1.4197677
Mean5616.9502
Median Absolute Deviation (MAD)2786
Skewness1.373846
Sum7.9423676 × 109
Variance29953469
MonotonicityNot monotonic
2024-04-22T17:23:38.638785image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 2828
 
0.2%
158 832
 
0.1%
30 772
 
0.1%
121 763
 
0.1%
92 720
 
0.1%
604 676
 
< 0.1%
59 634
 
< 0.1%
306 600
 
< 0.1%
40 596
 
< 0.1%
29 569
 
< 0.1%
Other values (23260) 1405010
99.4%
ValueCountFrequency (%)
10 2828
0.2%
11 101
 
< 0.1%
12 189
 
< 0.1%
13 253
 
< 0.1%
14 153
 
< 0.1%
15 178
 
< 0.1%
16 495
 
< 0.1%
17 160
 
< 0.1%
18 180
 
< 0.1%
19 413
 
< 0.1%
ValueCountFrequency (%)
25697 1
< 0.1%
25686 1
< 0.1%
25658 1
< 0.1%
25644 1
< 0.1%
25636 2
< 0.1%
25633 1
< 0.1%
25619 2
< 0.1%
25613 1
< 0.1%
25605 1
< 0.1%
25602 1
< 0.1%

reflectivity
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct5700
Distinct (%)3.0%
Missing1220984
Missing (%)86.3%
Infinite0
Infinite (%)0.0%
Mean6.7126096
Minimum-23.69
Maximum57.07
Zeros44
Zeros (%)< 0.1%
Negative56221
Negative (%)4.0%
Memory size10.8 MiB
2024-04-22T17:23:38.710896image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum-23.69
5-th percentile-13.43
Q1-1.7
median6.9
Q315.2625
95-th percentile26.18
Maximum57.07
Range80.76
Interquartile range (IQR)16.9625

Descriptive statistics

Standard deviation11.862737
Coefficient of variation (CV)1.7672317
Kurtosis-0.67080317
Mean6.7126096
Median Absolute Deviation (MAD)8.48
Skewness-0.022074791
Sum1295641
Variance140.72452
MonotonicityNot monotonic
2024-04-22T17:23:38.788570image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.88 90
 
< 0.1%
6.76 88
 
< 0.1%
10.02 88
 
< 0.1%
6.63 87
 
< 0.1%
8.28 86
 
< 0.1%
9.53 85
 
< 0.1%
7.23 84
 
< 0.1%
10.38 83
 
< 0.1%
6.84 82
 
< 0.1%
7.62 82
 
< 0.1%
Other values (5690) 192161
 
13.6%
(Missing) 1220984
86.3%
ValueCountFrequency (%)
-23.69 1
< 0.1%
-23.02 1
< 0.1%
-22.84 1
< 0.1%
-22.67 1
< 0.1%
-22.41 1
< 0.1%
-22.31 1
< 0.1%
-22.08 1
< 0.1%
-22.06 1
< 0.1%
-21.91 2
< 0.1%
-21.86 1
< 0.1%
ValueCountFrequency (%)
57.07 1
< 0.1%
53.27 1
< 0.1%
52.57 1
< 0.1%
52.56 1
< 0.1%
52.15 1
< 0.1%
50.35 1
< 0.1%
43.16 1
< 0.1%
42.85 1
< 0.1%
42 1
< 0.1%
40.77 2
< 0.1%

total_power
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7769
Distinct (%)2.1%
Missing1046362
Missing (%)74.0%
Infinite0
Infinite (%)0.0%
Mean10.400532
Minimum-19.74
Maximum78.98
Zeros97
Zeros (%)< 0.1%
Negative77157
Negative (%)5.5%
Memory size10.8 MiB
2024-04-22T17:23:38.937223image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum-19.74
5-th percentile-7.31
Q11.44
median9.24
Q318.1
95-th percentile31.14
Maximum78.98
Range98.72
Interquartile range (IQR)16.66

Descriptive statistics

Standard deviation12.160026
Coefficient of variation (CV)1.1691735
Kurtosis0.6941188
Mean10.400532
Median Absolute Deviation (MAD)8.27
Skewness0.636048
Sum3823630.7
Variance147.86624
MonotonicityNot monotonic
2024-04-22T17:23:39.011153image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.11 161
 
< 0.1%
6.39 156
 
< 0.1%
5.03 149
 
< 0.1%
7.13 149
 
< 0.1%
7.45 149
 
< 0.1%
7.56 148
 
< 0.1%
9.62 147
 
< 0.1%
7 146
 
< 0.1%
9.85 145
 
< 0.1%
7.71 145
 
< 0.1%
Other values (7759) 366143
 
25.9%
(Missing) 1046362
74.0%
ValueCountFrequency (%)
-19.74 1
< 0.1%
-18.52 1
< 0.1%
-18.48 1
< 0.1%
-18.27 1
< 0.1%
-18.02 1
< 0.1%
-17.81 1
< 0.1%
-17.69 1
< 0.1%
-17.65 1
< 0.1%
-17.64 1
< 0.1%
-17.57 1
< 0.1%
ValueCountFrequency (%)
78.98 1
< 0.1%
78.46 1
< 0.1%
77.1 1
< 0.1%
76.72 1
< 0.1%
76.28 1
< 0.1%
76.05 1
< 0.1%
75.77 1
< 0.1%
75.73 1
< 0.1%
75.68 1
< 0.1%
75.06 1
< 0.1%

velocity
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct4395
Distinct (%)2.9%
Missing1264638
Missing (%)89.4%
Infinite0
Infinite (%)0.0%
Mean-1.865443
Minimum-31.6
Maximum31.6
Zeros52
Zeros (%)< 0.1%
Negative93600
Negative (%)6.6%
Memory size10.8 MiB
2024-04-22T17:23:39.078665image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum-31.6
5-th percentile-11.8
Q1-7.48
median-2.74
Q33.31
95-th percentile10.53
Maximum31.6
Range63.2
Interquartile range (IQR)10.79

Descriptive statistics

Standard deviation7.4794865
Coefficient of variation (CV)-4.0094961
Kurtosis1.0127801
Mean-1.865443
Median Absolute Deviation (MAD)5.17
Skewness0.4062626
Sum-278626.3
Variance55.942718
MonotonicityNot monotonic
2024-04-22T17:23:39.150018image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-7.27 138
 
< 0.1%
-7.33 133
 
< 0.1%
-7.08 130
 
< 0.1%
-7.55 127
 
< 0.1%
-7.39 127
 
< 0.1%
-6.33 124
 
< 0.1%
-6.66 123
 
< 0.1%
-7.1 122
 
< 0.1%
-7.26 120
 
< 0.1%
-7.24 119
 
< 0.1%
Other values (4385) 148099
 
10.5%
(Missing) 1264638
89.4%
ValueCountFrequency (%)
-31.6 1
 
< 0.1%
-31.59 2
< 0.1%
-31.58 3
< 0.1%
-31.57 2
< 0.1%
-31.56 2
< 0.1%
-31.51 1
 
< 0.1%
-31.5 1
 
< 0.1%
-31.49 1
 
< 0.1%
-31.48 2
< 0.1%
-31.46 4
< 0.1%
ValueCountFrequency (%)
31.6 1
 
< 0.1%
31.59 1
 
< 0.1%
31.57 1
 
< 0.1%
31.56 1
 
< 0.1%
31.54 6
< 0.1%
31.53 1
 
< 0.1%
31.52 1
 
< 0.1%
31.51 3
< 0.1%
31.5 1
 
< 0.1%
31.49 1
 
< 0.1%

spectrum_width
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct662
Distinct (%)0.6%
Missing1299164
Missing (%)91.9%
Infinite0
Infinite (%)0.0%
Mean1.0823093
Minimum0.01
Maximum8.84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 MiB
2024-04-22T17:23:39.223022image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.24
Q10.57
median0.85
Q31.32
95-th percentile2.81
Maximum8.84
Range8.83
Interquartile range (IQR)0.75

Descriptive statistics

Standard deviation0.83274804
Coefficient of variation (CV)0.7694178
Kurtosis5.9382689
Mean1.0823093
Median Absolute Deviation (MAD)0.34
Skewness2.0638622
Sum124288.07
Variance0.69346929
MonotonicityNot monotonic
2024-04-22T17:23:39.291937image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 3086
 
0.2%
0.58 1093
 
0.1%
0.66 1092
 
0.1%
0.69 1092
 
0.1%
0.68 1086
 
0.1%
0.65 1085
 
0.1%
0.64 1074
 
0.1%
0.61 1068
 
0.1%
0.73 1065
 
0.1%
0.54 1062
 
0.1%
Other values (652) 102033
 
7.2%
(Missing) 1299164
91.9%
ValueCountFrequency (%)
0.01 3086
0.2%
0.02 15
 
< 0.1%
0.03 15
 
< 0.1%
0.04 27
 
< 0.1%
0.05 32
 
< 0.1%
0.06 48
 
< 0.1%
0.07 53
 
< 0.1%
0.08 60
 
< 0.1%
0.09 74
 
< 0.1%
0.1 82
 
< 0.1%
ValueCountFrequency (%)
8.84 1
< 0.1%
8.63 1
< 0.1%
8.47 1
< 0.1%
8.25 1
< 0.1%
7.62 1
< 0.1%
7.5 1
< 0.1%
7.41 2
< 0.1%
7.32 1
< 0.1%
7.29 1
< 0.1%
7.24 1
< 0.1%

time
Real number (ℝ)

HIGH CORRELATION 

Distinct316
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean175.98656
Minimum1
Maximum347
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 MiB
2024-04-22T17:23:39.358128image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22
Q192
median177
Q3264
95-th percentile332
Maximum347
Range346
Interquartile range (IQR)172

Descriptive statistics

Standard deviation99.438048
Coefficient of variation (CV)0.56503205
Kurtosis-1.1854954
Mean175.98656
Median Absolute Deviation (MAD)86
Skewness0.0047503565
Sum2.48845 × 108
Variance9887.9255
MonotonicityNot monotonic
2024-04-22T17:23:39.430736image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
292 5500
 
0.4%
331 5500
 
0.4%
310 5500
 
0.4%
112 5500
 
0.4%
223 5500
 
0.4%
231 5500
 
0.4%
141 5500
 
0.4%
104 5500
 
0.4%
283 5500
 
0.4%
39 5500
 
0.4%
Other values (306) 1359000
96.1%
ValueCountFrequency (%)
1 4500
0.3%
2 5000
0.4%
3 4000
0.3%
4 4000
0.3%
5 4500
0.3%
6 5000
0.4%
7 500
 
< 0.1%
12 1000
 
0.1%
13 5000
0.4%
14 5000
0.4%
ValueCountFrequency (%)
347 4000
0.3%
346 4500
0.3%
345 4500
0.3%
344 4500
0.3%
343 5000
0.4%
342 4500
0.3%
341 4500
0.3%
340 3500
0.2%
339 5000
0.4%
338 5000
0.4%

Interactions

2024-04-22T17:23:35.971264image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:31.641569image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:32.362006image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:33.052505image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:33.808557image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.367562image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.917356image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:35.442471image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:36.151431image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:31.763639image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:32.465632image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:33.161025image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:33.883811image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.446057image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.986247image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:35.502500image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:36.259784image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:31.870831image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:32.571429image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:33.266077image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:33.955614image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.515550image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:35.061427image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:35.564438image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:36.325555image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:31.933853image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:32.632517image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:33.327473image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.022779image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.585753image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:35.127412image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:35.624259image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:36.410651image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:32.011773image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:32.710283image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:33.404129image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.094172image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.661139image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:35.195577image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:35.689233image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:36.474974image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:32.076200image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:32.769563image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:33.470951image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.158138image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.721708image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:35.253311image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:35.743682image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:36.538106image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:32.141387image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:32.832749image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:33.627845image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.223498image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.781870image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:35.315219image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:35.800652image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:36.643958image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:32.249647image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:32.941462image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:33.739838image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.288808image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:34.849945image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:35.375440image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:23:35.858113image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Correlations

2024-04-22T17:23:39.484257image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
altitudelatitudelongitudereflectivityspectrum_widthtimetotal_powervelocity
altitude1.000-0.011-0.0180.342-0.4270.679-0.233-0.051
latitude-0.0111.000-0.018-0.145-0.060-0.016-0.0470.854
longitude-0.018-0.0181.0000.387-0.191-0.0540.2570.050
reflectivity0.342-0.1450.3871.000-0.134-0.0890.801-0.101
spectrum_width-0.427-0.060-0.191-0.1341.000-0.5140.0360.035
time0.679-0.016-0.054-0.089-0.5141.000-0.1810.147
total_power-0.233-0.0470.2570.8010.036-0.1811.000-0.034
velocity-0.0510.8540.050-0.1010.0350.147-0.0341.000

Missing values

2024-04-22T17:23:36.729267image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-22T17:23:37.107709image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

longitudelatitudealtitudereflectivitytotal_powervelocityspectrum_widthtime
010.659610106.72832510.0NaN17.01NaNNaN25.0
110.661768106.72834011.010.3722.41NaNNaN25.0
210.663927106.72835513.022.6046.00NaNNaN25.0
310.666085106.72836014.0NaN50.21NaNNaN25.0
410.668242106.72837016.0NaN49.70NaNNaN25.0
510.670402106.72838617.012.9935.050.061.4125.0
610.672560106.72840019.013.8236.21-4.620.0125.0
710.674717106.72841021.024.6430.7126.281.1925.0
810.676876106.72842422.012.2225.3025.561.4825.0
910.679034106.72843024.017.9632.42-4.910.3425.0
longitudelatitudealtitudereflectivitytotal_powervelocityspectrum_widthtime
141399011.691405106.71014424994.0NaNNaNNaNNaN342.0
141399111.693505106.71010625047.0NaNNaNNaNNaN342.0
141399211.695603106.71007025099.0NaNNaNNaNNaN342.0
141399311.697704106.71003025152.0NaNNaNNaNNaN342.0
141399411.699803106.70999025205.0NaNNaNNaNNaN342.0
141399511.701903106.70995025257.0NaNNaNNaNNaN342.0
141399611.704002106.70991525310.0NaNNaNNaNNaN342.0
141399711.706101106.70988525362.0NaNNaNNaNNaN342.0
141399811.708201106.70985025415.0NaNNaNNaNNaN342.0
141399911.710299106.70981025468.0NaNNaNNaNNaN342.0

Duplicate rows

Most frequently occurring

longitudelatitudealtitudereflectivitytotal_powervelocityspectrum_widthtime# duplicates
10410.65961106.72832510.0NaN16.66NaNNaN269.04
4210.65961106.72832510.0NaN16.08NaNNaN330.03
10810.65961106.72832510.0NaN16.70NaNNaN281.03
010.65961106.72832510.0NaN15.67NaNNaN90.02
110.65961106.72832510.0NaN15.68NaNNaN54.02
210.65961106.72832510.0NaN15.71NaNNaN54.02
310.65961106.72832510.0NaN15.75NaNNaN95.02
410.65961106.72832510.0NaN15.76NaNNaN175.02
510.65961106.72832510.0NaN15.80NaNNaN153.02
610.65961106.72832510.0NaN15.81NaNNaN32.02